Focused On-demand Library for Arginine-glutamic acid dipeptide repeats protein

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We use our state-of-the-art dedicated workflow for designing focused libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Key features that set our library apart include:

The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q9P2R6

UPID:

RERE_HUMAN

Alternative names:

Atrophin-1-like protein; Atrophin-1-related protein

Alternative UPACC:

Q9P2R6; O43393; O75046; O75359; Q5VXL9; Q6P6B9; Q9Y2W4

Background:

The Arginine-glutamic acid dipeptide repeats protein, also known as Atrophin-1-like protein or Atrophin-1-related protein, plays a pivotal role in cellular processes. It functions as a transcriptional repressor during development and is involved in cell survival regulation. Its overexpression leads to the recruitment of BAX to the nucleus, triggering caspase-3 activation and cell death.

Therapeutic significance:

Linked to a neurodevelopmental disorder with potential brain, eye, or heart anomalies, understanding the role of Arginine-glutamic acid dipeptide repeats protein could open doors to potential therapeutic strategies. Its involvement in transcriptional repression and cell survival pathways offers a promising avenue for targeted interventions in related diseases.